Scanner Data

We empirically compare the forecasting ability of artificial neural network (ANN) with multinomial logit model (MNL) in the context offrequently purchased grocery products for a retailer. Using scanner data on three grocery product categories, we find that performunce of ANN compares favorably to MNL in forecasting brand shares. We test the sensitivity of the forecasting error in the two approaches to the length of the estimation period and the clustering of households which is used to define homogenous segments of households. We find the results to be robust to these variations. We also derive a few empirical propositions regarding performance of ANN and MNL from our analysis. The results u-e consistent with those in Kumar, Rao and Soni (1995) and suggest that although neural networks suffer ,from interpretability problem, they are a useful method to forecast brand shares in grocery product categories where large amounts of scanner data are readily available. Artificial neural network (ANN) models are increasingly being used as a decision aid in a number of areas such as manufacturing, marketing, and retailing. Some applications in manufacturing have been in systems design, capacity planning, and product quality control (see Huang and Zhang, 1994 for a review of ANN applications in manufacturing). In marketing, applications have been reported in the areas of customer service, segmentation, and prospect identification (Shepard and Ratner, 1994; Venugopal and Baets, 1994). Some applications have also been reported in retailing particularly in fashion forecasting, retail assortment planning, and retail inventory management (Belt, 1993; Dragstedt, 1991). Retailers are also exploring neural networks to forecast retail demand in the grocery products industry (Thall, 1992). The use of neural networks in grocery retailing is especially appealing because large amounts of UPC (universal product code) scanner data routinely become available from the electronic check-out systems installed in the retail stores. Accurate demand forecasting is crucial for profitable retail operations because without a good

Stimulation of the vagus nerve in the neck can reduce seizures in epilepsy patients, and may be helpful in treating depression. PET studies have shown that vagus nerve stimulation (VNS) in epilepsy patients causes acute dose (intensity) dependent changes in regional cerebral blood flow. We sought to use the newly developed VNS synchronized fMRI technique to examine whether VNS BOLD signal changes depend on the frequency of stimulation. Six adults with recurrent depression were scanned inside a 1.5 T MR scanner. Data were acquired at rest, with the VNS device on for 7 s, and also, for comparison, while the patient listened to a tone for 7 s. In two separate back-to-back sessions, the VNS stimulation frequency was set to either 5 or 20 Hz. Data were transformed into Talairach space and then compared by condition. Compared to 5 Hz, 20 Hz VNS produced more acute activity changes from rest in regions similar to our initial VNS synchronized fMRI feasibility study in depression. Brain regions activated by hearing a tone were also greater when VNS was intermittently being applied at 20 Hz than at 5 Hz. In depressed adults, left cervical VNS causes regional brain activity changes that depend on the frequency of stimulation or total dose, or both. In addition to the acute immediate effects of VNS on regional brain activity, this study suggests further that VNS at different frequencies likely has frequency or dose dependent modulatory effects on other brain activities (e.g. hearing a tone). # (M. Lomarev).

B rain-computer interfaces (BCIs) utilize neurophysiological signals originating in the brain to activate or deactivate external devices or computers . Different neuroelectric signals have been used to control external devices, including EEG oscillations, electrocorticograms (ECoGs) from implanted electrodes, event-related potentials (ERPs) such as the P300 and slow cortical potential (SCP), short latency subcortical potentials and visually evoked potentials, and action potential spike trains from implanted multielectrodes. In comparison, the development of BCIs based on metabolic activity of the brain using two different imaging methods, functional magnetic resonance imaging (fMRI) [2] and functional near infrared spectroscopy [3], has been more recent.

The Jornada Experiment on the Jornada Experimental Range in southern New Mexico aims at the description of the surface energy balance of a desert grassland ecosystem. A large volume of both field and remote sensing data has been collected from 1995 to 1998. Airborne Daedalus scanner data with a spatial resolution of 4 rn have been used to infer the following land surface characteristics: surface temperature, albedo, and normalized difference vegetation index (NDVI). These land surface characteristics can be used as input for land surface models. However, land surface models work with very coarse grid cells of at least 50 x 50 km, in contrast to high-resolution remote sensing data. Also, land surface models are generally based on nonlinear algorithms. Both restrictions lead to scale problems. One apparent question is how to scale up input remote sensing data to the much coarser resolution of the land surface model. The first step is to derive the length scale of the input land surface characteristics. The length scales of the land surface characteristics have been determined with the following two techniques: autocorrelation and wavelet analysis. Within the Jornada Experimental Range, three different sites with different vegetation characteristics were distinguished: grass, shrub, and a transition site with patches of both grass and shrub. The autocorrelation and wavelet analysis showed similar results for the shrub site. For the grass and transition site the wavelet analysis underestimated the length scale of the surface albedo and temperature. The length scale of the surface albedo was 35, 33, and 10 rn for grass, transition, and shrub sites, respectively. The length scale of the surface temperature was 31, 20, and 8 rn for grass, transition, and shrub sites, respectively. The length scale of the NDVI was 12, 6, and 5 rn for grass, transition, and shrub sites, respectively. These small length scales could hamper the use of low-resolution remote sensing data for deriving input data for land surface models.

This paper employs a nation-wide sample of supermarket scanner data to estimate a large brand-level demand system for beer in the U.S. using the Distance Metric method of Pinkse, Slade and Brett [Pinkse, J., Slade, M., Brett, C., 2002. Spatial price competition: a semiparametric approach. Econometrica 70, . Unlike previous studies, this work estimates the own-and cross-advertising elasticities in addition to price elasticities. Positive and negative cross-advertising elasticities imply the presence of both cooperative and predatory effects of advertising expenditures across brands; however, the former effect appears to dominate suggesting that advertising increases the overall demand for beer. We discuss the implications of these results in this industry.

Fish is a low-fat protein source high in omega-3 fatty acids, but in 2004 consumers also heard that farmed salmon had high levels of polychlorinated biphenyl (PCBs). This research evaluated how Canadian consumers and processors reacted to the conflicting health messages. Demand estimates and time-series analysis of 2001-2006 frozen meat scanner data in Alberta, Canada show a significant drop in salmon expenditure share following the PCB finding. The industry responded by launching low-priced wild salmon products, which contributed to significant demand expansion. The analysis illustrates how a food safety threat was averted and even served as a catalyst for growth.

Scanner data for breakfast cereals are used to estimate demand elasticities for six supermarket stores in two distinct socio-economic areas. Three stores are in low-income locations and three are in high-income locations. A time series cross-section model is estimated for five product categories across six cross sections over forty-two weeks. Results show lower-income shoppers to have more elastic demands for

Neuroimaging studies in bipolar disorder report gray matter volume (GMV) abnormalities in neural regions implicated in emotion regulation, including ventral/orbital medial prefrontal cortex (OMPFC) GMV decreases and, more inconsistently, amygdala GMV increases. We aimed to examine OMPFC and amygdala GMV in bipolar disorder, type 1 patients (BPI) versus healthy control participants (HC), and examine potential confounding effects of gender, clinical and illness history variables and psychotropic medication upon any group differences that were demonstrated in OMPFC and amygdala GMV. Images were acquired from 27 BPI (17 euthymic, 10 depressed) and 28 age-and gender-matched HC in a 3T Siemens scanner. Data were analyzed with SPM5 using voxel-based morphometry to first examine main effects of diagnostic group and gender upon whole brain (WB) GMV. Post hoc analyses were subsequently performed to examine the extent to which clinical and illness history variables and psychotropic medication contributed to GMV abnormalities in BPI in a priori and non-a priori regions demonstrated by the above VBM analyses. Here, SPPSS was used to examine the effects of these variables on magnitude of GMV in these a priori and nona priori regions in BPI versus HC. BPI showed reduced GMV in two regions established a priori: bilateral posteromedial rectal gyrus (PMRG), but no amygdala GMV abnormalities. BPI also showed reduced GMV in two non-a priori regions: left parahippocampal gyrus and left putamen. For left PMRG GMV, there was a significant group by gender by trait anxiety interaction. GMV was significantly reduced in male low trait anxiety BPI versus male low trait anxiety HC, and in high versus low trait anxiety male BPI. Our findings show in BPI significant effects of male gender and high trait anxiety on GMV reduction in left PMRG, part of the OMPFC medial prefrontal network implicated in visceromotor and emotion regulation.

B rain-computer interfaces (BCIs) utilize neurophysiological signals originating in the brain to activate or deactivate external devices or computers . Different neuroelectric signals have been used to control external devices, including EEG oscillations, electrocorticograms (ECoGs) from implanted electrodes, event-related potentials (ERPs) such as the P300 and slow cortical potential (SCP), short latency subcortical potentials and visually evoked potentials, and action potential spike trains from implanted multielectrodes. In comparison, the development of BCIs based on metabolic activity of the brain using two different imaging methods, functional magnetic resonance imaging (fMRI) [2] and functional near infrared spectroscopy [3], has been more recent.

Scanner data for fast moving consumer goods typically amount to panels of time series where both N and T are large. To reduce the number of parameters and to shrink parameters towards plausible and interpretable values, Hierarchical Bayes models turn out to be useful. Such models contain in the second level a stochastic model to describe the parameters in the first level.

A simple experiment is used to examine the effect of grocery store nutrition labels on the sales of microwave popcorn in the East Bay area of California. Using an incomplete demand system we estimate the impact of the nutrition labels on sales of healthy (products that merit a nutrition label) and unhealthy (products that do not merit a nutrition label) microwave popcorn. Contrary to expectations, we find that nutrition labels decrease sales of healthy popcorn and increase sales of unhealthy popcorn across all stores. We speculate that nutrition labels on popcorn may signal unwanted product characteristics such as undesirable taste. Our findings highlight unintended effects created by nutrition labels. In terms of public welfare, it is important to consider not just the content of private industry nutrition labels but the effect they have on consumer behavior.

Most countries use either the Dutot or Jevons index number formula for the compilation of their consumer price index at the elementary level of aggregation. The difference between the formulas is shown to be accounted for by changes in price dispersion. In turn, some of this difference is shown to be explained by product heterogeneity. Scanner data on television sets (TVs) are used to calculate Dutot and Jevons indexes. The difference between them is successfully explained in terms of changes in price dispersion and much reduced using an hedonic, heterogeneity-controlled Dutot index. r

The use of 3D digitization and modeling in documenting heritage sites has increased significantly over the past few years. This is mainly due to advances in laser scanning techniques, 3D modeling software, image-based-modeling techniques, computer power, and virtual reality. There are many approaches currently available. The most common remains based on surveying and CAD tools and/or traditional photogrammetry with control points and a human operator. This is very time consuming and can be tedious and sustained effort. Lately, modeling methods based on scanners data and more automated image-based technique are becoming available. We will discuss each approach and point out its advantages and disadvantages. We will then present our approach, which is a combination of several technologies. The approach presented in this paper uses both interactive and automatic techniques, each where it is best suited, to accurately and completely model heritage objects and sites. A highly detailed st...

Using supermarket scanner data, we test a variety of hypotheses from trade journals about the invasion of private-label food products. According to conventional industry wisdom, name-brand firms defended their brands against new private-label products by lowering their prices, engaging in additional promotional activities, and increasingly differentiating their products. Our empirical evidence is inconsistent with these beliefs.

Rapidly available and accurate information about the location and extent of avalanche events is important for avalanche forecasting, safety assessments for roads and ski resorts, verification of warning products, as well as for hazard mapping and avalanche model calibration/validation. Today, observations from individual experts in the field provide isolated information with very limited coverage. This study presents a methodology for an automated, systematic and wide-area detection and mapping of avalanche deposits using optical remote sensing data of high spatial and radiometric resolution. A processing chain, integrating directional, textural and spectral information, is developed using ADS40 airborne digital scanner data acquired over a test site near Davos, Switzerland. Though certain limitations exist, encouraging detection and mapping accuracies can be reported. The presented approach is a promising addition to existing field observation methods for remote regions, and can be applied in otherwise inaccessible areas.

We study the link between price points and price rigidity using two data sets: weekly scanner data and Internet data. We find that ''9'' is the most frequent ending for the penny, dime, dollar, and ten-dollar digits; the most common price changes are those that keep the price endings at ''9''; 9-ending prices are less likely to change than non-9-ending prices; and the average size of price change is larger for 9-ending than non-9ending prices. We conclude that 9-ending contributes to price rigidity from penny to dollar digits and across a wide range of product categories, retail formats, and retailers. Nor does anyone know how important. .. [price points] are in practice.-Alan Blinder et al. (1998)

This paper analyzes the effect of TV advertising and in-store displays on the sales of chocolates. I examine which method is more effective in gaining customers and in increasing total sales. Also, I look at the evidence to see whether the lack of advertising by a firm will hurt the industry as a whole. In this paper, I use a nested logit model on scanner data obtained by the Zwick Center for Food and Resource Policy at the University of Connecticut to examine the effect of TV advertising on chocolate sales. The results show that in-store displays and advertising both help increase the demand for chocolate.

We study the link between price points and price rigidity using two data sets: weekly scanner data and Internet data. We find that ''9'' is the most frequent ending for the penny, dime, dollar, and ten-dollar digits; the most common price changes are those that keep the price endings at ''9''; 9-ending prices are less likely to change than non-9-ending prices; and the average size of price change is larger for 9-ending than non-9ending prices. We conclude that 9-ending contributes to price rigidity from penny to dollar digits and across a wide range of product categories, retail formats, and retailers. Nor does anyone know how important. .. [price points] are in practice.-Alan Blinder et al. (1998)

The Thanksgiving-Christmas holiday period is a major sales period for US retailers. Due to higher store traffic, tasks such as restocking shelves, handling customers' questions and inquiries, running cash registers, cleaning, and bagging, become more urgent during holidays. As a result, the holiday-period opportunity cost of price adjustment may increase dramatically for retail stores, which should lead to greater price rigidity during holidays. We test this prediction using weekly retail scanner price data from a major Midwestern supermarket chain. We find that indeed, prices are more rigid during holiday periods than non-holiday periods. For example, the econometric model we estimate suggests that the probability of a price change is lower during holiday periods, even after accounting for cost changes. Moreover, we find that the probability of a price change increases with the size of the cost change, during both, the holiday as well as non-holiday periods. We argue that these findings are best explained by higher price adjustment costs (menu cost) the retailers face during the holiday periods. Our data provides a natural experiment for studying variation in price rigidity because most aspects of market environment such as market structure, industry concentration, the nature of long-term relationships, contractual arrangements, etc., do not vary between holiday and nonholiday periods. We, therefore, are able to rule out these commonly used alternative explanations for the price rigidity, and conclude that the menu cost theory offers the best explanation for the holiday period price rigidity.

Neuroimaging studies in bipolar disorder report gray matter volume (GMV) abnormalities in neural regions implicated in emotion regulation, including ventral/orbital medial prefrontal cortex (OMPFC) GMV decreases and, more inconsistently, amygdala GMV increases. We aimed to examine OMPFC and amygdala GMV in bipolar disorder, type 1 patients (BPI) versus healthy control participants (HC), and examine potential confounding effects of gender, clinical and illness history variables and psychotropic medication upon any group differences that were demonstrated in OMPFC and amygdala GMV. Images were acquired from 27 BPI (17 euthymic, 10 depressed) and 28 age-and gender-matched HC in a 3T Siemens scanner. Data were analyzed with SPM5 using voxel-based morphometry to first examine main effects of diagnostic group and gender upon whole brain (WB) GMV. Post hoc analyses were subsequently performed to examine the extent to which clinical and illness history variables and psychotropic medication contributed to GMV abnormalities in BPI in a priori and non-a priori regions demonstrated by the above VBM analyses. Here, SPPSS was used to examine the effects of these variables on magnitude of GMV in these a priori and nona priori regions in BPI versus HC. BPI showed reduced GMV in two regions established a priori: bilateral posteromedial rectal gyrus (PMRG), but no amygdala GMV abnormalities. BPI also showed reduced GMV in two non-a priori regions: left parahippocampal gyrus and left putamen. For left PMRG GMV, there was a significant group by gender by trait anxiety interaction. GMV was significantly reduced in male low trait anxiety BPI versus male low trait anxiety HC, and in high versus low trait anxiety male BPI. Our findings show in BPI significant effects of male gender and high trait anxiety on GMV reduction in left PMRG, part of the OMPFC medial prefrontal network implicated in visceromotor and emotion regulation.

This article uses revealed preferences of consumers to study the consumer benefits from rBST-free and organic labeled milk. The article specifies and estimates a quadratic AIDS demand system model for different milk types using US supermarket scanner data. The introduction of rBST-free and organic milk is used to estimate consumer benefits, which are decomposed into two components, competitive and variety effects. Results show significant consumer benefits from organic milk and to a lesser extent from rBST-free milk. Based on the findings, we explore implications for present U.S. labeling standards.

This study uses revealed preferences of consumers to study the consumer valuations of rBST-free and organic milk. The study specifies and estimates a quadratic AIDS model for different milk types using US supermarket scanner data. The introduction of rBSTfree and organic milk is used to estimate both competitive and variety effects as measures of consumer valuations. Results show significant consumer valuations for organic milk and to a lesser extent rBST-free milk.

We investigate the theoretical possibility and empirical regularity of two troublesome anomalies that frequently arise when cross-price elasticities are estimated for a set of brands expected to be substitutes. These anomalies are the occurrence of: (a) negatively signed cross-elasticities; and (b) sign asymmetries in pairs of cross price elasticities. Drawing upon the Slutsky equation from neoclassical demand theory, we show

In this paper we present thermal characteristics of coal fires as measured during simulated fires under an experimental setting in Germany in July 2002. It is thus a continuation of the previously published paper "Thermal surface characteristics of coal fire 1: Results of in-situ measurement", in which we presented temperature measurements of real subsurface coal fires in China [Zhang, J., Kuenzer, C., accepted for publication. Thermal Surface Characteristics of Coal Fires 1: Results of in-situ measurements. Accepted for publication at Journal of Applied Geophysics.]. The focus is on simulated coal fires, which are less complex in nature than fires under natural conditions. In the present study we simulated all the influences usually occurring under natural conditions in a controllable manner (uniform background material of known thermal properties, known ventilation pathways, homogeneous coal substrate), creating two artificial outdoor coal fires under simplified settings. One surface coal fire and one subsurface coal fire were observed over the course of 2 days. The set up of the fires allowed for measurements not always feasible under "real" in-situ conditions: thus compared to the in-situ investigations presented in paper one we could retrieve numerous temperature measurements inside of the fires. Single temperature measurements, diurnal profiles and airborne thermal surveying present the typical temperature patterns of a small surface-and a subsurface fire under undisturbed conditions (easily accessible terrain, 24 hour measurements period, homogeneous materials). We found that the outside air temperature does not influence the fire's surface temperature (up to 900°C), while fire centre temperatures of up to 1200°C strongly correlate with surface temperatures of the fire. The fires could heat their surrounding up to a distance of 4.5 m. However, thermal anomalies on the background surface only persist as long as the fire is burning and disappear very fast if the heat source is removed. Furthermore, heat outside of the fires is transported mainly by convection and not by radiation. In spatial thermal line scanner data the diurnal thermal patterns of the coal fire are clearly represented. Our experiments during that data collection also visualize the thermal anomaly differences between covered (underground) and uncovered (surface) coal fires. The latter could not be observed in-situ in a real coal fire area. Subsurface coal fires express a much weaker signal than open surface fires and contrast only by few degrees against the background. In airborne thermal imaging scanner data the fires are also well represented. Here we could show that the mid-infrared domain (3.8 μm) is more suitable to pick up very hot anomalies, compared to the common thermal (8.8 μm) domain. Our results help to Author's personal copy understand coal fires and their thermal patterns as well as the limitations occurring during their analysis. We believe that the results presented here can practicably help for the planning of coal fire thermal mapping campaignsincluding remote sensing methods and the thermal data can be included into numerical coal fire modelling as initial or boundary conditions.

There are an increasing number of applications that require the construction of computerised human body models. The work presented here is a follow-up on a previously presented surface reconstruction algorithm, that has been greatly improved by following a local approach. The advantages of the method are presented, along with explanation of why its results are better compared to the previous algorithm. The result is a compound, multi-segment, and yet entirely smooth and watertight surface. Such a surface has a strong potential of being used for applications of a mainly medical nature, such as calculation of surface area and physical surface reconstruction for prosthetics manufacturing.

There are an increasing number of applications that require the construction of computerised human body models. Recently, Hamamatsu Photonics have developed an accurate and fast scanner based on position-sensitive photon detectors, capable of providing in a few seconds a dense (256x400 points) representation of the body. The work presented here is designed to exploit such a scanner's capabilities. An algorithm

We consider three approaches to estimating quality-adjusted price changes: (i) the dummy variable approach from a hedonic regression, (ii) a superlative or exact hedonic index and (iii) a matching technique-a technique akin to that used by statistical offices. The dummy variable approach is prevalent in the literature and has been used for independent estimates of quality changes when commenting on sources of error in consumer price indexes. However, the availability of scanner data provides an opportunity to utilize data on the prices (unit values), volumes and quality characteristics of a much wider range of transactions and to consider methods less restrictive than the dummy variable approach. The practical use of superlative or exact hedonic index and matching techniques using scanner data is explored, and the results from all three methods are compared. A feature of the paper is the breadth of the empirical work. It not only encompasses three different approaches, but extends across four different types of consumer durables. The manner in which the three approaches relate to each other is explored and the implications for quality-adjusted price changes is discussed.

© EARSeL and Warsaw University, Warsaw 2005. Proceedings of 4th EARSeL Workshop on Imaging Spectroscopy. New quality in environmental studies. Zagajewski B., Sobczak M., Wrzesień M., (eds) ... IMPLEMENTATION OF THE AUTOMATIC PROCESSING CHAIN FOR ARES

Fracture aperture is usually estimated by cubic law, which assumes flow between two smooth parallel plates. However, many researchers have proved that the fracture aperture is not a smooth surface but rather has tortuous paths and roughness and hence the flow behavior is different. Previous research showed that fracture aperture follows lognormal distribution. Nevertheless, there has not been any research conducted to validate the fracture aperture distribution with the change in stress conditions, which is common in fractured reservoirs. With the advent of X-ray CT scanner in the field of petroleum engineering, fracture apertures can be visualized and measured. Since there is no direct calculation for fracture aperture measurement from CT scanner data a calibration curve needs to be established. We developed a calibration curve based on existing calibration techniques, which involves area integration of the fracture region to obtain a correlation between integrated CT numbers and the calibrated fracture aperture. Using this calibration curve, we obtained distribution patterns for fracture apertures along the length of the core for various stress conditions, from about six thousand fracture aperture measurements for each stress condition. The results show that aperture distributions still follow lognormal distribution under various stress conditions.

A symmetric pricing or asymmetric price adjustment is the phenomenon where prices rise more readily than they fall. We offer and provide empirical support for a new theory of asymmetric pricing in wholesale prices. Wholesale prices may adjust asymmetrically in the small but symmetrically in the large, when retailers face cost of price adjustment. Such retailers will not adjust prices for small changes in their costs. Manufacturers then see a region of inelastic demand where small wholesale price changes do not translate into commensurate retail price changes. The implication is asymmetric-a small wholesale price increase is more profitable because manufacturers will not lose customers from higher retail prices; yet, a small decrease is less profitable, because it will not lower retail prices; hence, there is no extra revenue from greater sales. For larger changes, this asymmetry in the behavior of wholesale price vanishes as the price adjustment cost is compensated by the increase in retailers' revenue resulting from correspondingly large retail price changes. We present a formal economic model of a channel with forward-looking retailers and cost of price adjustment, test the derived propositions on the behavior of manufacturer prices using a large supermarket scanner data set, and find that the results are consistent with the predictions of our theory. We then discuss the implications for asymmetric pricing, channels, and cost of price adjustment literatures, as well as public policy.

In order to generate sales promotion response predictions, marketing analysts estimate demand models using either disaggregated (consumer-level) or aggregated (store-level) scanner data. Comparison of predictions from these demand models is complicated by the fact that models may accommodate different forms of consumer heterogeneity depending on the level of data aggregation. This study shows via simulation that demand models with various

The purpose of this investigation is the photogrammetric study of the geometric properties of aircraft multispectral scanner data. The research involves three areas; the use of Gauss-Markov processes in single strip rectification procedures, the use of spatial block adjustment techniques with multiple sidelapping strips, and the implementation of object space geometric constraints into aircraft MSS restitution algorithms.^ The research into Gauss-Markov processes involves the study of the theoretical nature of the processes and their application in a rigorous and efficient manner to aircraft MSS data restitution. Comparisons of the results using first and second order Gauss-Markov processes show that the second order process gives results equal to or slightly worse than those of the first order, while taking more execution time. The first order Gauss-Markov is therefore chosen as the optimum method.^ The spatial block adjustment algorithm was implemented using the collinearity techn...

This paper describes a new out-of-core multi-resolution data structure for real-time visualization and interactive editing of large point clouds. In addition, an editing system is discussed that makes use of the novel data structure to provide interactive editing tools for large scanner data sets. The new data structure provides efficient rendering and allows for handling very large data sets using out-of-core storage. Unlike related previous approaches, it also provides dynamic operations for online insertion, deletion and modification of points with time mostly independent of scene complexity. This permits local editing of huge models in real time while maintaining a full multi-resolution representation for visualization. The data structure is used to implement a prototypical editing system for large point clouds. It provides real-time local editing tools for huge data sets as well as a two-resolution scripting mode for planning large, non-local changes which are subsequently performed in an externally efficient offline computation. We evaluate our implementation on several synthetic and real-world examples of sizes up to 63GB.

This paper models consumer food choices with respect to different margarine and spread brands that include a new healthy brand. The results show that the older and smaller size households with higher income and higher education are more likely to purchase the healthy brand. An Almost Ideal Demand System for six brands was estimated and the coefficients were used to calculate price and brand expenditure elasticities in order to examine the responsiveness of the consumers to economic variables.